{"id":"W2270834142","doi":"10.4271/2000-01-0318","title":"Adding Value Through Predictive Analysis","year":2000,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Engineering and Test Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Chemicals (Canada)","funders":"","keywords":"Value (mathematics); Computer science; Predictive value; Machine learning; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006558459,0.001812969,0.00104368,0.002918466,0.001135296,0.008400945,0.00234305,0.001548445,0.02325303],"category_scores_gemma":[0.03893476,0.0006454385,0.001186489,0.002191932,0.002785737,0.008340884,0.00397061,0.003215075,0.004297088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002634717,"about_ca_system_score_gemma":0.003396081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007234174,"about_ca_topic_score_gemma":0.006342482,"domain_scores_codex":[0.9960194,0.001458209,0.0001354319,0.0005038769,0.001623349,0.0002597185],"domain_scores_gemma":[0.9845468,0.01010887,0.000528672,0.002091616,0.002415906,0.0003081114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001223194,0.0001568899,0.003919926,0.0002521191,0.0001194289,0.0002576037,0.0004444929,0.1108974,0.0004900558,0.5611866,0.02211542,0.3000379],"study_design_scores_gemma":[0.00002636364,0.00005019749,0.0004700722,0.0002503332,0.00007474704,0.00008160166,0.0002943726,0.3410597,0.000644428,0.6256307,0.03136642,0.00005111617],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01248989,0.002257643,0.8517445,0.009536857,0.0005298819,0.0002623707,0.0004802867,0.002081146,0.1206174],"genre_scores_gemma":[0.5319444,0.004944827,0.4272472,0.001781659,0.000873844,0.0005283635,0.0009550279,0.0009784956,0.03074626],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02325303,"threshold_uncertainty_score":0.07778913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007741912572369339,"score_gpt":0.2200810633859706,"score_spread":0.2123391508136013,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}